# -*- coding: utf-8 -*-
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from datetime import timedelta
from jms.dim.dim_lmdm_sys_network import jms_dim__dim_lmdm_sys_network
from jms.dwd.dwd_wide_tms_trunk_shipno_road_waybill_dt import jms_dwd__dwd_wide_tms_trunk_shipno_road_waybill_dt

jms_dm__dm_design_vehicle_ontime_detail_dt = SparkSqlOperator(
    task_id='jms_dm__dm_design_vehicle_ontime_detail_dt',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    #execution_timeout=timedelta(hours=2)
    #excel平均时长:2分26秒
    execution_timeout = timedelta(minutes=30),
    email=['suning@jtexpress.com','yl_bigdata@yl-scm.com'],
    name='jms_dm__dm_design_vehicle_ontime_detail_dt_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dm/dm_design_vehicle_ontime_detail_dt/execute.hql',
    executor_cores=2,
    executor_memory='4G',
    num_executors=4,  # spark.dynamicAllocation.enabled 为 True 时，num_executors 表示最少 Executor 数
    conf={'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
          'spark.shuffle.service.enabled' : 'true',  # 动态资源 Shuffle 服务开启
          #'spark.dynamicAllocation.maxExecutors'  : 16,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.maxExecutors'  : 11,  # 动态资源最大扩容 Executor 数
          'spark.dynamicAllocation.cachedExecutorIdleTimeout': 60,  # 动态资源自动释放闲置 Executor 的超时时间(s)
          'spark.sql.sources.partitionOverwriteMode' : 'dynamic',  # 允许删改已存在的分区
          'spark.executor.memoryOverhead'  : '1G',  # 堆外内存
          'spark.sql.shuffle.partitions'  : 600,
          },
    hiveconf={'hive.exec.dynamic.partition' : 'true',  # 动态分区
             'hive.exec.dynamic.partition.mode' : 'nonstrict',
             'hive.exec.max.dynamic.partitions' : 400,  # 每天生成 20 个分区
             'hive.exec.max.dynamic.partitions.pernode': 400,  # 每天生成 20 个分区
             },
)

jms_dm__dm_design_vehicle_ontime_detail_dt << [
    jms_dim__dim_lmdm_sys_network,
    jms_dwd__dwd_wide_tms_trunk_shipno_road_waybill_dt,
]


